Triple

T23951649
Position Surface form Disambiguated ID Type / Status
Subject Korean FA Cup E603061 entity
Predicate relatedCompetition P2357 FINISHED
Object Korean Super Cup
The Korean Super Cup was an annual football match in South Korea that traditionally opened the season by pitting the K League champions against the Korean FA Cup winners.
E1608133 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Korean Super Cup | Statement: [Korean FA Cup, relatedCompetition, Korean Super Cup]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Korean Super Cup
Triple: [Korean FA Cup, relatedCompetition, Korean Super Cup]
Generated description
The Korean Super Cup was an annual football match in South Korea that traditionally opened the season by pitting the K League champions against the Korean FA Cup winners.

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69e2953e4924819093f1c24c03476b42 completed April 17, 2026, 8:17 p.m.
NER Named-entity recognition batch_69f1d03204348190a82876778d9cdd63 completed April 29, 2026, 9:32 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f76554dc88190a0448f4b707f9864 completed May 21, 2026, 9:17 p.m.
NEDg Description generation batch_6a0f7763b168819096e38c871623606d completed May 21, 2026, 9:21 p.m.
NED2 Entity disambiguation (via description) batch_6a0f78495eb481908d64e7caa0e065b4 completed May 21, 2026, 9:25 p.m.
Created at: April 17, 2026, 9:20 p.m.